Predicting risk for acute coronary syndromes (ACS) remains an inexact science. Although several recent risk prediction algorithms have been proposed, the original and most widely used system is from the Framingham Heart Study. The Framingham Risk Score (FRS) was designed to predict the 10-year risk for major coronary events, and it does so with a c-statistic [area under the receiver operating characteristic (ROC) curve] of 0.7-0.8. All of these prediction algorithms generally include age, sex, total (or low-density lipoprotein, LDL) cholesterol (C), high-density lipoprotein C (HDL-C), blood pressure and smoking and diabetic status when assigning risk. Despite the utility of the FRS in coronary heart disease (CHD) risk prediction, there remains a need for additional markers that improve upon this standard; while a number of putative risk factors have been tested, few have added meaningfully to the FRS.